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Background: The COVID-19 pandemic has spurred large-scale, inter-institutional research efforts. To enable these efforts, the German Corona Consensus (GECCO) dataset has been developed previously as a harmonized, interoperable collection of the most relevant data elements for COVID-19-related patient research. As GECCO has been developed as a compact core dataset across all medical fields, the focused research within particular medical domains demanded the definition of extension modules that include those data elements that are most relevant to the research performed in these individual medical specialties.
Main body: We created GECCO extension modules for the immunization, pediatrics, and cardiology domains with respect to the pandemic requests. The data elements included in each of these modules were selected in a consensus-based process by working groups of medical experts from the respective specialty to ensure that the contents are aligned with the research needs of the specialty. The selected data elements were mapped to international standardized vocabularies and data exchange specifications were created using HL7 FHIR profiles on the appropriate resources. All steps were performed in close interdisciplinary collaboration between medical domain experts, medical information scientists and FHIR developers. The profiles and vocabulary mappings were syntactically and semantically validated in a two-stage process. In that way, we defined dataset specifications for a total number of 23 (immunization), 59 (pediatrics), and 50 (cardiology) data elements that augment the GECCO core dataset. We created and published implementation guides and example implementations as well as dataset annotations for each extension module.
Conclusions: We here present extension modules for the GECCO core dataset that contain data elements most relevant to COVID-19-related patient research in immunization, pediatrics and cardiology. These extension modules were defined in an interdisciplinary, iterative, consensus-based approach that may serve as a blueprint for the development of further dataset definitions and GECCO extension modules. The here developed GECCO extension modules provide a standardized and harmonized definition of specialty-related datasets that can help to enable inter-institutional and cross-country COVID-19 research in these specialties.
Background The COVID-19 pandemic has spurred large-scale, inter-institutional research efforts. To enable these efforts, researchers must agree on dataset definitions that not only cover all elements relevant to the respective medical specialty but that are also syntactically and semantically interoperable. Following such an effort, the German Corona Consensus (GECCO) dataset has been developed previously as a harmonized, interoperable collection of the most relevant data elements for COVID-19-related patient research. As GECCO has been developed as a compact core dataset across all medical fields, the focused research within particular medical domains demands the definition of extension modules that include those data elements that are most relevant to the research performed in these individual medical specialties.
Objective To (i) specify a workflow for the development of interoperable dataset definitions that involves a close collaboration between medical experts and information scientists and to (ii) apply the workflow to develop dataset definitions that include data elements most relevant to COVID-19-related patient research in immunization, pediatrics, and cardiology.
Methods We developed a workflow to create dataset definitions that are (i) content-wise as relevant as possible to a specific field of study and (ii) universally usable across computer systems, institutions, and countries, i.e., interoperable. We then gathered medical experts from three specialties (immunization, pediatrics, and cardiology) to the select data elements most relevant to COVID-19-related patient research in the respective specialty. We mapped the data elements to international standardized vocabularies and created data exchange specifications using HL7 FHIR. All steps were performed in close interdisciplinary collaboration between medical domain experts and medical information scientists. The profiles and vocabulary mappings were syntactically and semantically validated in a two-stage process.
Results We created GECCO extension modules for the immunization, pediatrics, and cardiology domains with respect to the pandemic requests. The data elements included in each of these modules were selected according to the here developed consensus-based workflow by medical experts from the respective specialty to ensure that the contents are aligned with the respective research needs. We defined dataset specifications for a total number of 48 (immunization), 150 (pediatrics), and 52 (cardiology) data elements that complement the GECCO core dataset. We created and published implementation guides and example implementations as well as dataset annotations for each extension module.
Conclusions These here presented GECCO extension modules, which contain data elements most relevant to COVID-19-related patient research in immunization, pediatrics and cardiology, were defined in an interdisciplinary, iterative, consensus-based workflow that may serve as a blueprint for the development of further dataset definitions. The GECCO extension modules provide a standardized and harmonized definition of specialty-related datasets that can help to enable inter-institutional and cross-country COVID-19 research in these specialties.
Folgende Publikationen werden rezensiert: Garve & al.: Verbreitungsatlas Niedersachsen, Hölzel & al.: Stromtalwiesen, Lübcke & Frede: Naturschutzgebiete in Hessen Band 4, Notizbuch 68 der Kasseler Schule, Riecken & al.: Rote Liste Biotoptypen, Schulz & Dengler: Verbreitungsatlas Moose Schleswig-Holstein, Szabo: Wandern – Erkennen – Heilen
Im Rahmen einer hessenweiten Untersuchung wurden etwa 70 künstliche Stillgewässer – Kiesgruben, Tagebaurestseen, Fischteiche – auf das Vorkommen von Wasserpflanzen untersucht.
Die Untersuchung erbrachte den Nachweis von 78 Taxa, darunter 59 Arten Höherer Pflanzen und 19 Arten Characeen. Rund 25 % der nachgewiesnen Arten sind in der Roten Liste des Landes Hessen aufgeführt. Einige der nachgewiesenen Arten galten als verschollen. Von herausragender Bedeutung sind Kiesgruben in der Untermain- und Oberrhein-ebene, wo bis zu 10 Characeen-Arten in einem Gewässer nachgewiesen werden konnten. Von bundesweiter Bedeutung sind Funde von Nitella confervacea, N. tenuissima, Tolypella glomerata, T. intricata und T. prolifera. Als weit häufiger als erwartet erwies sich Potamogeton trichoides, die in allen Untersuchungsbereichen festgestellt wurde. Elodea nuttallii ist in den untersuchten Gewässern deutlich häufiger als E. canadensis. Sehr stark als Vogelrastplatz genutzte Teiche in der Wetterau zeigen, offenbar bedingt durch den Nährstoffeintrag durch Wasservögel, eine deutliche Eutrophierung.
Zur Schließung von Kenntnislücken zur Flora der Gewässer Hessens wurden 2009 von der BVNH neun Altarme von Rhein und Main untersucht. Die Ergeb-nisse zeigen, dass viele als sehr selten oder verschollen geltende Gewässermakrophyten noch oder wieder in den Altarmen des hessischen Oberrheinabschnitts zu finden sind. Insgesamt wurden 51 Arten nachgewiesen, darunter fünf Armleuchteralgen.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
Festuca rhenana spec. nov. und Festuca heteropachys, zwei verkannte Schwingel der Flora Deutschlands
(2012)
Seit über vier Jahrzehnten werden kräftige Schwingel von Silikatfelsen des mittelrheinischen Raumes irrtümlich als Festuca heteropachys bezeichnet. Diese Pflanzen gehören zu keiner der bisher bekannten Sippen. Sie werden unter dem Namen F. rhenana als neue, in Deutschland endemische Art beschrieben. Im Nordpfälzer Bergland, im Nahe- , im Mittelrhein- und im Moseltal besiedelt F. rhenana extrem trocken-warme Felsstandorte auf ± basenreichen Silikatgesteinen (Rhyolith, Andesit, Oberrotliegendes, devonische Schiefer). Fast alle Fundorte liegen in Rheinland-Pfalz, zwei in Hessen. Die wahre F. heteropachys kommt ebenfalls in Deutschland vor, und zwar nur im südlichen Teil von Rheinland-Pfalz. F. heteropachys ist ein mesophiles bis schwach thermophiles, Halbschatten ertragendes Horstgras. Kennzeichnend sind die mit 30–50 cm oft sehr langen Grundblätter und die starke, deutlich bis über die Mitte der Halme reichende Beblätterung. Im Anschluss an die Vorkommen im Elsass findet sich F. heteropachys hauptsächlich im Pfälzer Wald auf ± sauren steinigen oder sandigen Böden über Buntsandstein. Unterscheidungsmerkmale von F. heteropachys, F. rhenana, F. lemanii und der häufigen F. guestfalica werden dargestellt.
Hexaploides Chenopodium album ist in Frankfurt am Main (Hessen) häufig. Die Pflanzen unterscheiden sich deutlich in Blütezeit, Höhe, Verzweigung, Blattform und Blütenstandsmorphologie, wobei oft morphologisch einheitliche Pflanzen benachbart wachsen. Die Merkmale variieren unabhängig voneinander und es erscheint nicht sinnvoll, morphologische Gruppen taxonomisch zu fassen.
A central motivation for the development of x-ray free-electron lasers has been the prospect of time-resolved single-molecule imaging with atomic resolution. Here, we show that x-ray photoelectron diffraction—where a photoelectron emitted after x-ray absorption illuminates the molecular structure from within—can be used to image the increase of the internuclear distance during the x-ray-induced fragmentation of an O2 molecule. By measuring the molecular-frame photoelectron emission patterns for a two-photon sequential K-shell ionization in coincidence with the fragment ions, and by sorting the data as a function of the measured kinetic energy release, we can resolve the elongation of the molecular bond by approximately 1.2 a.u. within the duration of the x-ray pulse. The experiment paves the road toward time-resolved pump-probe photoelectron diffraction imaging at high-repetition-rate x-ray free-electron lasers.